A Conceptual Approach to Time Savings and Cost Competitiveness Assessments for Drone Transport of Biologic Samples with Unmanned Aerial Systems (Drones)

SanJeeVni: Secure UAV-Envisioned Massive Vaccine Distribution for COVID-19 Underlying 6G Network

Recently, unmanned aerial vehicles (UAVs) are deployed in Novel Coronavirus Disease-2019 (COVID-19) vaccine distribution process. To address issues of fake vaccine distribution, real-time massive UAV monitoring and control at nodal centers (NCs), the authors propose SanJeeVni, a blockchain (BC)-assisted UAV vaccine distribution at the backdrop of sixth-generation (6G) enhanced ultra-reliable low latency communication (6G-eRLLC) communication. The scheme considers user registration, vaccine request, and distribution through a public Solana BC setup, which assures a scalable transaction rate. Based on vaccine requests at production setups, UAV swarms are triggered with vaccine delivery to NCs. An intelligent edge offloading scheme is proposed to support UAV coordinates and routing path setups. The scheme is compared against fifth-generation (5G) uRLLC communication. In the simulation, we achieve and 86% improvement in service latency, 12.2% energy reduction of UAV with 76.25% more UAV coverage in 6G-eRLLC, and a significant improvement of [Formula: see text]% in storage cost against the Ethereum network, which indicates the scheme efficacy in practical setups.

The impact of environmental factors on external and internal specimen transport

The environment that a clinical specimen is exposed to is an important preanalytical factor in laboratory testing. There are numerous environmental conditions that a specimen may experience before it arrives at the clinical laboratory for analysis. Specimens collected at offsite locations are typically stored at the site and transported to the clinical laboratory via courier. Depending on the geographic location, season, method of storage and method of transport, the specimen can experience varying climate conditions that can lead to inaccurate test results. Specimens collected within the healthcare institution are not exempt from suboptimal storage and transport environments. For example, specimens transported via pneumatic tube systems can experience extreme agitation and rapid accelerations and decelerations. Suboptimal storage and transport temperatures occur less frequently within health systems due to multiple regulatory requirements for temperature monitoring; however, temperature monitoring may not occur at every stage of the preanalytical phase. This review will highlight both internal and external environmental conditions that can cause preanalytical errors in clinical laboratory testing. Strategies to mitigate environmentally-induced preanalytical errors and regulatory gaps for environmental monitoring in the preanalytical phase will also be discussed.

Drone Usage for Medicine and Vaccine Delivery during the COVID-19 Pandemic: Attitude of Health Care Workers in Rural Medical Centres

Rural areas are often difficult to access reliably with medicine and vaccines. This study aimed to examine rural health care workers’ attitude towards drone delivery for medicine and vaccines and the factors that influenced it. Health care workers from four rural health care facilities were sampled. Participants self-reported their demographic information, attitude towards medicine and vaccine delivery using drones, perception of benefits and risks of using drones, and perceived leadership innovativeness through an online or a pen-and-paper questionnaire. A total of 272 health care workers (mean age = 36.19, SD = 8.10) from all of the sites participated in this study. More than half of the study participants agreed or strongly agreed that using a drone to deliver medicine and vaccines is a good idea (54.2%, 95% CI [47.5, 60.8]), a wise idea (54.6%, 95% CI [47.9, 61.2]), and is desirable (52.5%, 95% CI [45.7, 59.0]). Males (β = 0.223), workers from the Obstetrics and Gynaecology department (β = 0.135), a lower perceived delivery risk (β = −0.237), and higher leadership innovativeness (β = 0.336) predicted positive attitudes towards drone usage. Assistant medical officers (β = −0.172) had a negative attitude. There is a need to further understand the roles of occupation and leadership innovativeness in predicting health care workers’ attitude towards drone usage, as these differences could be embedded within their roles in the health care system.